Through most of history, marketing was that touchy-feely part of an organization. with no data to defend itself. As a result, its budget was always the first one cut. That’s not longer true. Marketing leaders in every vertical are now laser-focused on precise customer insights that they can use to implement and measure the success of their marketing plans. That doesn’t mean the CMO budget is bigger; it means CMOs must do more with less. They must deploy against the right data, make the right media buys, and be prepared to provide attribution numbers.

This isn’t just a budget issue; it’s also a brand safety issue. Companies are becoming more careful about where to run advertisements, for example, knowing that their ads could run alongside an offensive message or one that simply does not align with the character of the brand they represent.

So what are the best CMOs doing? They are investing in martech. Martech, at the very least, is a cover-your-butt technology that can help show the boss they made the right spend and the campaign worked. Most experienced CMOs who know their brands and their customers have really good intuition, but intuition is not enough anymore. It also helps to have predictive analytics.

According to Forrester Research, marketers who have adopted predictive analytics are twice as likely to exceed their revenue targets. On the other hand, most martech is not “mature” yet:

We didn’t quite find a solution that provides boatloads of intelligence about new or existing targets, reveals purchase timing, demonstrates built-in intuition about optimally designed content, and delivers that content via a customer’s desired channel – all provided with “set it and forget it” automation. Delivering on that vision is still off in the future.

But we did find that predictive marketing analytics has a place in a balanced B2B marketing technology portfolio since the category powers three distinct but core responsibilities: ongoing nurture for known accounts, cultivation of anonymous contacts at unknown accounts and, and finally, identification of new accounts showing signals of interest in a firm’s portfolio of services and offerings.

Right now, predictive analytics can only provide good buyer profiles and perhaps a sense of the propensity to buy. There’s still a big problem in using technology to find those customers who will buy:

Yet, predictive analytics are only as helpful as their data inputs, and the data sets marketers can access at this time are still fairly rudimentary when it comes to tracking true indicators of influence. Neuroscience has uncovered that decision-making is almost completely emotional, rather than rational. However, our data collection methods are not yet mature enough to provide meaningful emotional analytics at scale.

Eventually, technology will advance to the point that it can recognize and analyze physical responses tied to emotion, such as the heat I emit from my hand into my phone, or the expansion of my retina in response to a compelling piece of content. Until machines can make systematic sense of the complexity of human emotional response, we will not have tapped into the full potential of predictive analytics.

Olenski: Putting the customer front and center is key for ANY brand’s success. How can CMOs spearhead the creation of customer-centric organizations to increase their bottom line?

Hatch: Building data-driven marketing cultures has become a major role of the CMO, and it requires a complete rewiring of marketing operations. Designing organizational workflows and architecting technology around these data flows is the key to enabling a customer-centric marketing organization that drives business value.